TOCS Event

There
is growing interest in brain-like computing, but can machines think like
humans? Associative memories learn by example like humans. We present the
world's fastest triple store -Saffron Memory Base- for just in time machine
learning. Saffron Memory Base uncovers connections, counts
and context in the raw data. It builds a semantic graph out of the box from hybrid data sources. Saffron stores the graph and its statistics in
matrices that can be queried in real time even for Big Data.

Connecting
the Dots. We
demonstrate the power of entity rank for real time search by the example of the
London Bomber and Twitter sentiment analysis.

Illuminating
the Dots. We
show the power of Saffron's model-free approach for pattern recognition and
prediction on a couple of real world examples like Boeing's use case of
predictive maintenance for aircraft.

Speaker Bio:

Dr. Paul Hofmann is an expert in AI, computer simulations, and graphics. He is CTO of Saffron Technology, a Big Data software analytics firm named top 5 coolest vendors in Enterprise Information Management by Gartner. Before joining Saffron, Paul was VP of Research at SAP Labs in Silicon Valley. Paul received his Ph.D. in Physics at the Darmstadt University of Technology.

Paul's background is entrenched in research as Senior Scientist and Assistant Professor at outstanding European and American Universities (Northwestern University, U.S.; Munich University of Technology and Darmstadt University of Technology, Germany). He is an expert in computational chemistry (Ph.D., research and teaching in Nonlinear Dynamics and Chaos Theory), authoring numerous publications and books. Paul was visiting scientist at MIT, Cambridge in 2009.